Introduction
Bone marrow biopsy is performed in a number of health and cancer related work to determine the dissemination status of a solid tumor; the cause of anemia, the determination of leukemia or lymphoma and the monitoring of response to treatment.
Determining bone marrow cellularity is often a subjective estimation with great interobserver variation. A rapid, accurate, reproducible method would be desirable for pathologists who regularly examine bone marrow biopsies.
The optical microscope in the diagnostic and biomedical laboratory is routinely used by pathologists and research scientist to make diagnosis and perform experiments. These users perform these functions by visualizing cells and tissue sections that have been previously prepared and chemically stained in the histology or histochemistry laboratory. Every patient with a tumor suspected of cancer undergoes evaluation and staging of the disease to determine if there is dissemination or systemic spread. The bone marrow biopsy is used to determine systemic disease. This bone marrow tissue is routinely fixed in formalin, processed in a tissue processor, embedded in formalin and serially cut in a microtome to give thin sections representing the diagnostic material.
The existing diagnosis is performed by examining the tissue optically using the objective lenses of the microscope in low and high power magnifications. The routinely stained hematoxylin and eosin tissue is examined first to visualize first in low power the overall bone marrow cellularity and an estimate is performed by the pathologist. This estimate is included in the report as part of the patient record. There is as yet no automated way to determine bone marrow cellularity using a robust, reproducible and objective manner. Crucial clinical decisions are made on this subjective interpretation of the bone marrow cellularity. The information is used for determining diagnosis, treatment response and monitoring and exclusion or inclusion in certain clinical therapeutic protocols.
The routinely stained hematoxylin and eosin tissue is examined and the overall bone marrow cellularity is estimated by the pathologist. The latter practice is the standard of practice, not because it is the optimal way, but because of an absence of an automated bone marrow cellularity measuring tool associated with the microscope. This practice is subjective, error prone, and often gives wide range of results that depends on the level of microscopist's skill.
Using advance segmentation algorithm employed in the present invention, chromogen-marked microscopic bone marrow digitized images are automatically evaluated and results projected for the pathologists within a short period of time with minimal variance and great reproducibility regardless of the type of stain; hematoxylin and eosin (‘H&E’) or Periodic Acid Schiff (‘PAS’). Accordingly, the results are highly correlated with the pathologists as set forth in the detailed embodiment.
The present invention further performs a series of biopsies stained with routine H&E or PAS and their corresponding images were used to generate the validation data. The results are useful, rapid and accurate way to extract bone marrow cellularity and provide a cell to fat ratio. An accurate, rapid measurement of bone marrow cellularity would be beneficial to practicing pathologists.
Prior Art
U.S. Publication No. 20070020697 published on Jan. 25, 2007 to Cualing et al. reveals an automated method of single cell image analysis which determines cell population statistic, applicable in the field of pathology, disease or cancer diagnosis, in a greatly improved manner over manual or prior art scoring techniques. This invention does not provide an algorithm for determining bone marrow cellularity result which provides a fat to cell ratio.
U.S. Publication No. 20060280352 published on Dec. 14, 2006 to Bryan et al. reveals a computer-implemented method for analyzing images which may include quantitatively analyzing image data to identify image objects relative to a background portion of the image according to predefined object criteria, the image data including a plurality of image objects that represent objects in a sample distributed across a substrate. The identified image objects are further clustered into groups or colonies of the identified image objects according to predetermined clustering criteria. However, the method is applicable only to bone marrow cultured cells and stroma on culture dishes used in a laboratory and experimental setup, and not in a daily pathology diagnostic practice as intended by the present invention. Moreover, no output like a cell to fat ratio or quantitative immunohistochemistry is used by this invention; therefore, no cellularity result is determined.
WIPO Publication No. 2007080583 published on Jul. 19, 2007 to Kolatt et al. reveals methods, computer readable storage media and systems which can be used for analyzing labeled biological samples, identifying chromosomal aberrations, identifying genetically abnormal cells and/or computationally scanning the samples using randomly or randomized scanning methods; wherein, said samples comprises a tissue biopsy from a bone marrow sample. This invention does not provide any thresholding and segmentation algorithms, and morphometric image analysis for determining bone marrow cellularity and does not provide a cell to fat ratio output.
U.S. Publication No. 20020067858 published on Jun. 6, 2002 to Lazaridis reveals a system, process, and computer program product for extracting quantitative summaries of information from digital images which includes performing a first image analysis and one or more additional image analyses. This invention does not disclose any thresholding and segementation algorithm to provide cellularity results for a bone marrow tissue through a cell to fat ratio output.
Nilsson et al., in the publication entitled, “Segmentation of Complex Cell Clusters in Microscopic Images: Application to Bone Marrow Samples,” published in Cytometry, volume 66(1), pages 24-31 on July 2005, presents an algorithm that enables image analysis-based analysis of bone marrow samples for the first time and may also be adopted for other digital cytometric applications where separation of complex cell clusters is required. This microscopic image analysis deals not with tissue or bone marrow tissue section but with clusters of bone marrow cells smeared on a microscopic slide. Algorithm optimizes declustering of the cells of bone marrow smear or cytologic preparation which tend to form large clusters when prepared in the laboratory. No output like a cell to fat ratio is provided therein, hence, it does not provide a bone marrow cellularity result.